



'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__          =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__          =  {
    'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}


class 					snake_case			(lowerCamelCase__ ):
       lowerCAmelCase__	:Optional[int]     =       "xglm"
       lowerCAmelCase__	:str     =       ["past_key_values"]

       lowerCAmelCase__	:List[str]     =       {
           "num_attention_heads": "attention_heads",
           "hidden_size": "d_model",
           "num_hidden_layers": "num_layers",
       }



       def __init__(					self  ,UpperCAmelCase_=256_008  ,UpperCAmelCase_=2_048  ,UpperCAmelCase_=1_024  ,UpperCAmelCase_=4_096  ,UpperCAmelCase_=24  ,UpperCAmelCase_=16  ,UpperCAmelCase_="gelu"  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=0.1  ,UpperCAmelCase_=0.0  ,UpperCAmelCase_=0.0  ,UpperCAmelCase_=0.02  ,UpperCAmelCase_=True  ,UpperCAmelCase_=True  ,UpperCAmelCase_=2  ,UpperCAmelCase_=1  ,UpperCAmelCase_=0  ,UpperCAmelCase_=2  ,**UpperCAmelCase_  ,)	->				Union[str, Any]:
           lowercase__									=    vocab_size
           lowercase__									=    max_position_embeddings
           lowercase__									=    d_model
           lowercase__									=    ffn_dim
           lowercase__									=    num_layers
           lowercase__									=    attention_heads
           lowercase__									=    activation_function
           lowercase__									=    dropout
           lowercase__									=    attention_dropout
           lowercase__									=    activation_dropout
           lowercase__									=    layerdrop
           lowercase__									=    init_std
           lowercase__									=    scale_embedding  # scale factor will be sqrt(d_model) if True
           lowercase__									=    use_cache

           super().__init__(
               pad_token_id=__snake_case  ,bos_token_id=__snake_case  ,eos_token_id=__snake_case  ,decoder_start_token_id=__snake_case  ,**__snake_case  ,)









'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
     from PIL import Image

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       """Salesforce/blip-image-captioning-base"""
    lowercase__					=       (
        """This is a tool that generates a description of an image. It takes an input named `image` which should be the """
        """image to caption, and returns a text that contains the description in English."""
    )
    lowercase__					=       """image_captioner"""
    lowercase__					=       AutoModelForVisionaSeq

    lowercase__					=       ["""image"""]
    lowercase__					=       ["""text"""]







    def __init__( self					:    Tuple		,     *__snake_case					:    int		,     **__snake_case					:    List[Any]      ):
      requires_backends(self		,     ['vision']      )
      super().__init__(*__snake_case		,     **__snake_case      )







    def      lowercase_			( self					:    Optional[int]		,     __snake_case					:    "Image"      ):
      return self.pre_processor(images=__snake_case		,     return_tensors='pt'      )







    def      lowercase_			( self					:    Optional[Any]		,     __snake_case					:    str      ):
      return self.model.generate(**__snake_case      )







    def      lowercase_			( self					:    Optional[Any]		,     __snake_case					:    Tuple      ):
      return self.pre_processor.batch_decode(__snake_case		,     skip_special_tokens=__snake_case      )[0].strip()